configurable txt separator

NN/training/samples/curl.txt

@@ -0,0 +1,24 @@
+so, curl example:
+curl http://localhost:1234/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "deepseek-r1-0528-qwen3-8b",
+    "messages": [
+      { "role": "system", "content": "what will be the next row in this sequence:
+symbol	MAIN SYMBOL (ETH)																								REF1 (BTC)					REF2 (SPX)					REF3 (SOL)
+timeframe	1s						1m					1h						1d							1s					1s					1s
+datapoint	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp
+2025-01-15T10:00:00Z	3421.5	3421.75	3421.25	3421.6	125.4	2025-01-15T10:00:00Z	3422.1	3424.8	3420.5	3423.25	1245.7	2025-01-15T10:00:00Z	3420	3428.5	3418.75	3425.1	12847.2	2025-01-15T10:00:00Z	3415.25	3435.6	3410.8	3430.4	145238.6	2025-01-15T10:00:00Z	97850.2	97852.4	97848.1	97851.3	8.7	2025-01-15T10:00:00Z	5925.4	5926.1	5924.8	5925.7	0	2025-01-15T10:00:00Z	191.22	191.45	191.08	191.35	1247.3
+2025-01-15T10:00:01Z	3421.6	3421.85	3421.45	3421.75	98.2	2025-01-15T10:01:00Z	3423.25	3425.9	3421.8	3424.6	1189.3	2025-01-15T11:00:00Z	3425.1	3432.2	3422.4	3429.8	11960.5	2025-01-16T10:00:00Z	3430.4	3445.2	3425.15	3440.85	138947.1	2025-01-15T10:00:01Z	97851.3	97853.8	97849.5	97852.9	9.1	2025-01-15T10:00:01Z	5925.7	5926.3	5925.2	5925.9	0	2025-01-15T10:00:01Z	191.35	191.58	191.15	191.48	1156.7
+2025-01-15T10:00:02Z	3421.75	3421.95	3421.55	3421.8	110.6	2025-01-15T10:02:00Z	3424.6	3427.15	3423.4	3425.9	1356.8	2025-01-15T12:00:00Z	3429.8	3436.7	3427.2	3434.5	13205.9	2025-01-17T10:00:00Z	3440.85	3455.3	3438.9	3450.75	142568.3	2025-01-15T10:00:02Z	97852.9	97855.2	97850.7	97854.6	7.9	2025-01-15T10:00:02Z	5925.9	5926.5	5925.4	5926.1	0	2025-01-15T10:00:02Z	191.48	191.72	191.28	191.61	1298.4
+2025-01-15T10:00:03Z	3421.8	3422.05	3421.65	3421.9	87.3	2025-01-15T10:03:00Z	3425.9	3428.4	3424.2	3427.1	1423.5	2025-01-15T13:00:00Z	3434.5	3441.8	3432.1	3438.2	14087.6	2025-01-18T10:00:00Z	3450.75	3465.4	3448.6	3460.2	149825.7	2025-01-15T10:00:03Z	97854.6	97857.1	97852.3	97856.8	8.4	2025-01-15T10:00:03Z	5926.1	5926.7	5925.6	5926.3	0	2025-01-15T10:00:03Z	191.61	191.85	191.42	191.74	1187.9
+2025-01-15T10:00:04Z	3421.9	3422.15	3421.75	3422.0	134.7	2025-01-15T10:04:00Z	3427.1	3429.6	3425.8	3428.3	1298.2	2025-01-15T14:00:00Z	3438.2	3445.6	3436.4	3442.1	12734.8	2025-01-19T10:00:00Z	3460.2	3475.8	3457.4	3470.6	156742.4	2025-01-15T10:00:04Z	97856.8	97859.4	97854.9	97858.2	9.2	2025-01-15T10:00:04Z	5926.3	5926.9	5925.8	5926.5	0	2025-01-15T10:00:04Z	191.74	191.98	191.55	191.87	1342.6
+2025-01-15T10:00:05Z	3422.0	3422.25	3421.85	3422.1	156.8	2025-01-15T10:05:00Z	3428.3	3430.8	3426.9	3429.5	1467.9	2025-01-15T15:00:00Z	3442.1	3449.3	3440.7	3446.8	11823.4	2025-01-20T10:00:00Z	3470.6	3485.2	3467.9	3480.1	163456.8	2025-01-15T10:00:05Z	97858.2	97860.7	97856.4	97859.8	8.8	2025-01-15T10:00:05Z	5926.5	5927.1	5926.0	5926.7	0	2025-01-15T10:00:05Z	191.87	192.11	191.68	192.0	1278.5
+
+      " },
+      { "role": "user", "content": "2025-01-15T10:00:06Z" }
+    ],
+    "temperature": 0.7,
+    "max_tokens": -1,
+    "stream": false
+}'

NN/training/samples/readme.md

@@ -9,3 +9,8 @@ datapoint	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V
 2025-01-15T10:00:03Z	3421.8	3422.05	3421.65	3421.9	87.3	2025-01-15T10:03:00Z	3425.9	3428.4	3424.2	3427.1	1423.5	2025-01-15T13:00:00Z	3434.5	3441.8	3432.1	3438.2	14087.6	2025-01-18T10:00:00Z	3450.75	3465.4	3448.6	3460.2	149825.7	2025-01-15T10:00:03Z	97854.6	97857.1	97852.3	97856.8	8.4	2025-01-15T10:00:03Z	5926.1	5926.7	5925.6	5926.3	0	2025-01-15T10:00:03Z	191.61	191.85	191.42	191.74	1187.9
 2025-01-15T10:00:04Z	3421.9	3422.15	3421.75	3422.0	134.7	2025-01-15T10:04:00Z	3427.1	3429.6	3425.8	3428.3	1298.2	2025-01-15T14:00:00Z	3438.2	3445.6	3436.4	3442.1	12734.8	2025-01-19T10:00:00Z	3460.2	3475.8	3457.4	3470.6	156742.4	2025-01-15T10:00:04Z	97856.8	97859.4	97854.9	97858.2	9.2	2025-01-15T10:00:04Z	5926.3	5926.9	5925.8	5926.5	0	2025-01-15T10:00:04Z	191.74	191.98	191.55	191.87	1342.6
 2025-01-15T10:00:05Z	3422.0	3422.25	3421.85	3422.1	156.8	2025-01-15T10:05:00Z	3428.3	3430.8	3426.9	3429.5	1467.9	2025-01-15T15:00:00Z	3442.1	3449.3	3440.7	3446.8	11823.4	2025-01-20T10:00:00Z	3470.6	3485.2	3467.9	3480.1	163456.8	2025-01-15T10:00:05Z	97858.2	97860.7	97856.4	97859.8	8.8	2025-01-15T10:00:05Z	5926.5	5927.1	5926.0	5926.7	0	2025-01-15T10:00:05Z	191.87	192.11	191.68	192.0	1278.5
+
+
+
+
+

NN/training/samples/txt/market_data_20250826_2129.txt

@@ -0,0 +1,4 @@
+symbol	MAIN SYMBOL (ETH)																									REF1 (BTC)						REF2 (SPX)						REF3 (SOL)
+timeframe	1s						1m						1h						1d						1s						1s						1s
+datapoint	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp	O	H	L	C	V	Timestamp
+2025-08-26T21:29:44Z	0	0	0	0	0	2025-08-26T21:29:44Z	0	0	0	0	0	2025-08-26T21:29:44Z	0	0	0	0	0	2025-08-26T21:29:44Z	0	0	0	0	0	2025-08-26T21:29:44Z	0	0	0	0	0	2025-08-26T21:29:44Z	5500.00	5520.00	5495.00	5510.00	1000000.0	2025-08-26T21:29:44Z	0	0	0	0	0	2025-08-26T21:29:44Z

core/enhanced_reward_calculator.py

@@ -302,12 +302,13 @@ class EnhancedRewardCalculator:
         normalized_mse = min(mse / max_mse, 1.0)
         mse_reward = np.exp(-5 * normalized_mse)  # Exponential decay, range [exp(-5), 1]
         
-        # Direction accuracy bonus/penalty
+        # Direction accuracy bonus/penalty (stronger punishment for wrong direction)
         direction_correct = (prediction.predicted_direction == actual_direction)
-        direction_bonus = 0.5 if direction_correct else -0.5
+        # Increase wrong-direction penalty; reduce correct-direction bonus slightly
+        direction_bonus = 0.25 if direction_correct else -1.0
         
-        # Confidence scaling
+        # Confidence scaling (apply floor to avoid near-zero scaling)
-        confidence_weight = prediction.confidence
+        confidence_weight = max(prediction.confidence, 0.2)
         
         # Final reward calculation
         base_reward = mse_reward + direction_bonus

core/orchestrator.py

@@ -7042,7 +7042,9 @@ class TradingOrchestrator:
                 'main_symbol': self.symbol,
                 'ref1_symbol': self.ref_symbols[0] if self.ref_symbols else 'BTC/USDT',
                 'ref2_symbol': 'SPX',  # Default to SPX for now
-                'export_dir': 'NN/training/samples/txt'
+                'ref3_symbol': 'SOL/USDT',
+                'export_dir': 'NN/training/samples/txt',
+                'export_format': 'PIPE'
             }
             
             self.text_export_manager.export_config.update(export_config)

core/text_data_exporter.py

@@ -44,7 +44,9 @@ class TextDataExporter:
                  export_dir: str = "NN/training/samples/txt",
                  main_symbol: str = "ETH/USDT",
                  ref1_symbol: str = "BTC/USDT", 
-                 ref2_symbol: str = "SPX"):
+                 ref2_symbol: str = "SPX",
+                 ref3_symbol: str = "SOL/USDT",
+                 export_format: str = "PIPE"):
         """
         Initialize text data exporter
         
@@ -60,6 +62,8 @@ class TextDataExporter:
         self.main_symbol = main_symbol
         self.ref1_symbol = ref1_symbol
         self.ref2_symbol = ref2_symbol
+        self.ref3_symbol = ref3_symbol
+        self.export_format = export_format.upper() if isinstance(export_format, str) else "PIPE"
         
         # Timeframes to export
         self.timeframes = ['1s', '1m', '1h', '1d']
@@ -77,7 +81,7 @@ class TextDataExporter:
         os.makedirs(self.export_dir, exist_ok=True)
         
         logger.info(f"Text Data Exporter initialized - Export dir: {self.export_dir}")
-        logger.info(f"Symbols: MAIN={main_symbol}, REF1={ref1_symbol}, REF2={ref2_symbol}")
+        logger.info(f"Symbols: MAIN={main_symbol}, REF1={ref1_symbol}, REF2={ref2_symbol}, REF3={ref3_symbol}")
     
     def start(self):
         """Start the data export process"""
@@ -140,7 +144,8 @@ class TextDataExporter:
         symbols = [
             ("MAIN", self.main_symbol),
             ("REF1", self.ref1_symbol), 
-            ("REF2", self.ref2_symbol)
+            ("REF2", self.ref2_symbol),
+            ("REF3", self.ref3_symbol)
         ]
         
         for symbol_type, symbol in symbols:
@@ -168,11 +173,27 @@ class TextDataExporter:
     def _get_latest_data(self, symbol: str, timeframe: str) -> Optional[MarketDataPoint]:
         """Get latest market data for symbol/timeframe"""
         try:
-            if not hasattr(self.data_provider, 'get_latest_candle'):
+            candle = None
-                return None
+            # Try direct method
-                
+            if hasattr(self.data_provider, 'get_latest_candle'):
-            # Try to get latest candle data
                 candle = self.data_provider.get_latest_candle(symbol, timeframe)
+            # Fallback to historical last row
+            if (not candle) and hasattr(self.data_provider, 'get_historical_data'):
+                try:
+                    df = self.data_provider.get_historical_data(symbol, timeframe, limit=1)
+                    if df is not None and not df.empty:
+                        latest = df.iloc[-1]
+                        ts = df.index[-1]
+                        candle = {
+                            'open': latest.get('open', 0),
+                            'high': latest.get('high', 0),
+                            'low': latest.get('low', 0),
+                            'close': latest.get('close', 0),
+                            'volume': latest.get('volume', 0),
+                            'timestamp': ts.to_pydatetime() if hasattr(ts, 'to_pydatetime') else ts
+                        }
+                except Exception as _ex:
+                    logger.debug(f"hist fallback failed for {symbol} {timeframe}: {_ex}")
             if not candle:
                 return None
             
@@ -205,8 +226,10 @@ class TextDataExporter:
                 grouped_data = self._group_data_by_symbol(export_data)
                 
                 with open(filepath, 'w', encoding='utf-8') as txtfile:
-                    # Write in the format specified in readme.md sample
+                    if self.export_format == 'TAB':
                         self._write_tab_format(txtfile, grouped_data)
+                    else:
+                        self._write_pipe_format(txtfile, grouped_data)
                         
                 logger.debug(f"Exported {len(export_data)} data points to {filepath}")
                 
@@ -280,57 +303,106 @@ class TextDataExporter:
         rows.append(row)
         return rows
     
-    def _write_tab_format(self, txtfile, grouped_data: Dict[str, Dict[str, Dict[str, Any]]]):
+    def _write_tab_format(self, txtfile, grouped_data: Dict[str, Dict[str, Dict[str, Any]]] ):
         """Write data in tab-separated format like readme.md sample"""
         # Write header structure
-        txtfile.write("symbol\tMAIN SYMBOL (ETH)\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tREF1 (BTC)\t\t\t\t\t\tREF2 (SPX)\t\t\t\t\t\tREF3 (SOL)\n")
+        txtfile.write("symbol\tMAIN SYMBOL (ETH)\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tREF1 (BTC)\t\t\t\t\t\t\tREF2 (SPX)\t\t\t\t\t\t\tREF3 (SOL)\n")
         txtfile.write("timeframe\t1s\t\t\t\t\t\t1m\t\t\t\t\t\t1h\t\t\t\t\t\t1d\t\t\t\t\t\t1s\t\t\t\t\t\t1s\t\t\t\t\t\t1s\n")
         txtfile.write("datapoint\tO\tH\tL\tC\tV\tTimestamp\tO\tH\tL\tC\tV\tTimestamp\tO\tH\tL\tC\tV\tTimestamp\tO\tH\tL\tC\tV\tTimestamp\tO\tH\tL\tC\tV\tTimestamp\tO\tH\tL\tC\tV\tTimestamp\tO\tH\tL\tC\tV\tTimestamp\n")
         
-        # Write data row
+        # Build up to 300 rows using historical 1s data when available
-        row_parts = []
+        # Collect timestamps from MAIN 1s historical data
-        current_time = datetime.now()
+        timestamps: List[Any] = []
+        hist_df = None
+        try:
+            if hasattr(self.data_provider, 'get_historical_data'):
+                hist_df = self.data_provider.get_historical_data(self.main_symbol, '1s', limit=300)
+                if hist_df is not None and not hist_df.empty:
+                    timestamps = list(hist_df.index[-300:])
+        except Exception as _e:
+            logger.debug(f"hist 1s not available: {_e}")
+        if not timestamps:
+            timestamps = [datetime.utcnow()]
 
-        # Timestamp first
+        # Fetch snapshots for non-1s
-        row_parts.append(current_time.strftime("%Y-%m-%dT%H:%M:%SZ"))
-        
-        # ETH data for all timeframes (1s, 1m, 1h, 1d)
         main_data = grouped_data.get('MAIN', {})
-        for timeframe in ['1s', '1m', '1h', '1d']:
+        main_1m = main_data.get('1m')
-            data_point = main_data.get(timeframe)
+        main_1h = main_data.get('1h')
-            if data_point:
+        main_1d = main_data.get('1d')
+        ref1_1s = grouped_data.get('REF1', {}).get('1s')
+        ref2_1s = grouped_data.get('REF2', {}).get('1s')
+        ref3_1s = grouped_data.get('REF3', {}).get('1s')
+
+        for ts in timestamps:
+            try:
+                ts_str = ts.strftime("%Y-%m-%dT%H:%M:%SZ") if hasattr(ts, 'strftime') else str(ts)
+            except Exception:
+                ts_str = ""
+            row_parts = [ts_str]
+
+            # MAIN 1s from hist row if possible
+            if hist_df is not None and ts in hist_df.index:
+                r = hist_df.loc[ts]
                 row_parts.extend([
-                    f"{data_point['open']:.2f}",
+                    f"{float(r.get('open', 0) or 0):.2f}",
-                    f"{data_point['high']:.2f}",
+                    f"{float(r.get('high', 0) or 0):.2f}",
-                    f"{data_point['low']:.2f}",
+                    f"{float(r.get('low', 0) or 0):.2f}",
-                    f"{data_point['close']:.2f}",
+                    f"{float(r.get('close', 0) or 0):.2f}",
-                    f"{data_point['volume']:.1f}",
+                    f"{float(r.get('volume', 0) or 0):.1f}",
-                    data_point['timestamp'].strftime("%Y-%m-%dT%H:%M:%SZ")
+                    ts_str
                 ])
             else:
-                row_parts.extend(["0", "0", "0", "0", "0", current_time.strftime("%Y-%m-%dT%H:%M:%SZ")])
+                snap = main_data.get('1s')
-        
+                if snap:
-        # REF1 (BTC), REF2 (SPX), REF3 (SOL) - 1s timeframe only
-        for ref_type in ['REF1', 'REF2']:  # REF3 will be added by LLM proxy
-            ref_data = grouped_data.get(ref_type, {})
-            data_point = ref_data.get('1s')
-            if data_point:
                     row_parts.extend([
-                    f"{data_point['open']:.2f}",
+                        f"{snap['open']:.2f}", f"{snap['high']:.2f}", f"{snap['low']:.2f}", f"{snap['close']:.2f}", f"{snap['volume']:.1f}", ts_str
-                    f"{data_point['high']:.2f}",
-                    f"{data_point['low']:.2f}",
-                    f"{data_point['close']:.2f}",
-                    f"{data_point['volume']:.1f}",
-                    data_point['timestamp'].strftime("%Y-%m-%dT%H:%M:%SZ")
                     ])
                 else:
-                row_parts.extend(["0", "0", "0", "0", "0", current_time.strftime("%Y-%m-%dT%H:%M:%SZ")])
+                    row_parts.extend(["0", "0", "0", "0", "0", ts_str])
 
-        # Add placeholder for REF3 (SOL) - will be filled by LLM proxy
+            # MAIN 1m/1h/1d snapshots
-        row_parts.extend(["0", "0", "0", "0", "0", current_time.strftime("%Y-%m-%dT%H:%M:%SZ")])
+            for snap in [main_1m, main_1h, main_1d]:
+                if snap:
+                    row_parts.extend([
+                        f"{snap['open']:.2f}", f"{snap['high']:.2f}", f"{snap['low']:.2f}", f"{snap['close']:.2f}", f"{snap['volume']:.1f}", snap['timestamp'].strftime("%Y-%m-%dT%H:%M:%SZ")
+                    ])
+                else:
+                    row_parts.extend(["0", "0", "0", "0", "0", ts_str])
+
+            # REF1/REF2/REF3 1s snapshots
+            for snap in [ref1_1s, ref2_1s, ref3_1s]:
+                if snap:
+                    row_parts.extend([
+                        f"{snap['open']:.2f}", f"{snap['high']:.2f}", f"{snap['low']:.2f}", f"{snap['close']:.2f}", f"{snap['volume']:.1f}", snap['timestamp'].strftime("%Y-%m-%dT%H:%M:%SZ")
+                    ])
+                else:
+                    row_parts.extend(["0", "0", "0", "0", "0", ts_str])
 
             txtfile.write("\t".join(row_parts) + "\n")
 
+    def _write_pipe_format(self, txtfile, grouped_data: Dict[str, Dict[str, Dict[str, Any]]] ):
+        """Write data in pipe-delimited console-friendly grid."""
+        from io import StringIO
+        buffer = StringIO()
+        self._write_tab_format(buffer, grouped_data)
+        content = buffer.getvalue().splitlines()
+        if not content:
+            return
+        headers = [line.split('\t') for line in content[:3]]
+        data_rows = [line.split('\t') for line in content[3:]]
+
+        def to_pipe(row: List[str]) -> str:
+            return "|" + "|".join(str(col) for col in row) + "|"
+
+        # Render header rows with separators
+        for hdr in headers:
+            txtfile.write(to_pipe(hdr) + "\n")
+            txtfile.write("|" + "|".join(["-" * max(3, len(str(c))) for c in hdr]) + "|\n")
+
+        # Render data
+        for row in data_rows:
+            txtfile.write(to_pipe(row) + "\n")
+    
     def get_current_filename(self) -> Optional[str]:
         """Get current export filename"""
         return self.current_filename

core/text_export_integration.py

@@ -33,7 +33,9 @@ class TextExportManager:
             'main_symbol': 'ETH/USDT',
             'ref1_symbol': 'BTC/USDT',
             'ref2_symbol': 'SPX',  # Will need to be mapped to available data
-            'export_dir': 'NN/training/samples/txt'
+            'ref3_symbol': 'SOL/USDT',
+            'export_dir': 'NN/training/samples/txt',
+            'export_format': 'PIPE'  # PIPE (default) or TAB
         }
     
     def initialize_exporter(self, config: Optional[Dict[str, Any]] = None):
@@ -54,7 +56,9 @@ class TextExportManager:
                 export_dir=self.export_config['export_dir'],
                 main_symbol=self.export_config['main_symbol'],
                 ref1_symbol=self.export_config['ref1_symbol'],
-                ref2_symbol=self.export_config['ref2_symbol']
+                ref2_symbol=self.export_config['ref2_symbol'],
+                ref3_symbol=self.export_config.get('ref3_symbol', 'SOL/USDT'),
+                export_format=self.export_config.get('export_format', 'PIPE')
             )
             
             logger.info("Text data exporter initialized successfully")
@@ -198,16 +202,8 @@ class EnhancedDataProviderWrapper:
     
     def _get_spx_data(self) -> Optional[Dict[str, Any]]:
         """Get SPX data - placeholder for now"""
-        # For now, return mock SPX data
+        # No synthetic data allowed; return None if not available
-        # In production, this would connect to a stock data provider
+        return None
-        return {
-            'open': 5500.0,
-            'high': 5520.0,
-            'low': 5495.0,
-            'close': 5510.0,
-            'volume': 1000000,
-            'timestamp': datetime.now()
-        }
 
 # Integration helper functions
 def setup_text_export(data_provider=None, orchestrator=None, config: Optional[Dict[str, Any]] = None) -> TextExportManager:

web/clean_dashboard.py

@@ -1921,6 +1921,86 @@ class CleanTradingDashboard:
                 logger.error(f"Error closing position manually: {e}")
                 return [html.I(className="fas fa-times me-1"), "CLOSE"]
         
+        # Text Export Controls
+        @self.app.callback(
+            Output('text-export-status', 'children'),
+            [Input('start-text-export-btn', 'n_clicks'),
+             Input('stop-text-export-btn', 'n_clicks')],
+            prevent_initial_call=True
+        )
+        def handle_text_export_controls(start_clicks, stop_clicks):
+            """Handle text export start/stop buttons"""
+            ctx = dash.callback_context
+            if not ctx.triggered:
+                raise PreventUpdate
+            
+            button_id = ctx.triggered[0]['prop_id'].split('.')[0]
+            
+            try:
+                if button_id == 'start-text-export-btn' and start_clicks:
+                    success = self.orchestrator.start_text_export()
+                    if success:
+                        logger.info("Text export started from dashboard")
+                        return "Export: Running"
+                    else:
+                        logger.error("Failed to start text export")
+                        return "Export: Failed to start"
+                        
+                elif button_id == 'stop-text-export-btn' and stop_clicks:
+                    success = self.orchestrator.stop_text_export()
+                    if success:
+                        logger.info("Text export stopped from dashboard")
+                        return "Export: Stopped"
+                    else:
+                        logger.error("Failed to stop text export")
+                        return "Export: Failed to stop"
+                        
+            except Exception as e:
+                logger.error(f"Error in text export controls: {e}")
+                return f"Export: Error - {str(e)}"
+            
+            raise PreventUpdate
+        
+        # LLM Proxy Controls
+        @self.app.callback(
+            Output('llm-status', 'children'),
+            [Input('start-llm-btn', 'n_clicks'),
+             Input('stop-llm-btn', 'n_clicks')],
+            prevent_initial_call=True
+        )
+        def handle_llm_controls(start_clicks, stop_clicks):
+            """Handle LLM proxy start/stop buttons"""
+            ctx = dash.callback_context
+            if not ctx.triggered:
+                raise PreventUpdate
+            
+            button_id = ctx.triggered[0]['prop_id'].split('.')[0]
+            
+            try:
+                if button_id == 'start-llm-btn' and start_clicks:
+                    success = self.orchestrator.start_llm_proxy()
+                    if success:
+                        logger.info("LLM proxy started from dashboard")
+                        return "LLM: Running"
+                    else:
+                        logger.error("Failed to start LLM proxy")
+                        return "LLM: Failed to start"
+                        
+                elif button_id == 'stop-llm-btn' and stop_clicks:
+                    success = self.orchestrator.stop_llm_proxy()
+                    if success:
+                        logger.info("LLM proxy stopped from dashboard")
+                        return "LLM: Stopped"
+                    else:
+                        logger.error("Failed to stop LLM proxy")
+                        return "LLM: Failed to stop"
+                        
+            except Exception as e:
+                logger.error(f"Error in LLM controls: {e}")
+                return f"LLM: Error - {str(e)}"
+            
+            raise PreventUpdate
+        
         # Leverage slider callback
         @self.app.callback(
             Output('leverage-display', 'children'),
@@ -2899,7 +2979,7 @@ class CleanTradingDashboard:
             hold_predictions = []
             
             for pred in dqn_predictions[-30:]:  # Last 30 DQN predictions
-                action = pred.get('action', 2)  # 0=BUY, 1=SELL, 2=HOLD
+                action = pred.get('action', 2)  # 0=SELL, 1=HOLD, 2=BUY
                 confidence = pred.get('confidence', 0)
                 timestamp = pred.get('timestamp', datetime.now())
                 price = pred.get('price', 0)
@@ -2916,9 +2996,10 @@ class CleanTradingDashboard:
                         'q_values': pred.get('q_values', [0, 0, 0])
                     }
                     
-                    if action == 0:  # BUY
+                    # Correct mapping: 2 -> BUY, 0 -> SELL, 1 -> HOLD
+                    if action == 2:  # BUY
                         buy_predictions.append(pred_data)
-                    elif action == 1:  # SELL
+                    elif action == 0:  # SELL
                         sell_predictions.append(pred_data)
                     else:  # HOLD
                         hold_predictions.append(pred_data)
@@ -3329,10 +3410,6 @@ class CleanTradingDashboard:
         try:
             predictions = []
             
-            # Generate sample predictions if needed (for display purposes)
-            if hasattr(self.orchestrator, 'generate_sample_predictions_for_display'):
-                self.orchestrator.generate_sample_predictions_for_display(symbol)
-            
             # Get REAL predictions from orchestrator
             if hasattr(self.orchestrator, 'recent_dqn_predictions'):
                 predictions.extend(list(self.orchestrator.recent_dqn_predictions.get(symbol, [])))

web/layout_manager.py

@@ -320,6 +320,33 @@ class DashboardLayoutManager:
                         html.I(className="fas fa-arrows-rotate me-1"),
                         "Sync Positions/Orders"
                     ], id="manual-sync-btn", className="btn btn-primary btn-sm w-100 mt-2"),
+                    
+                    # Text Export Controls
+                    html.Hr(className="my-2"),
+                    html.Small("Text Export & LLM", className="text-muted d-block mb-1"),
+                    html.Div([
+                        html.Button([
+                            html.I(className="fas fa-file-export me-1"),
+                            "Start Text Export"
+                        ], id="start-text-export-btn", className="btn btn-success btn-sm me-1", style={"fontSize": "10px"}),
+                        html.Button([
+                            html.I(className="fas fa-stop me-1"),
+                            "Stop"
+                        ], id="stop-text-export-btn", className="btn btn-danger btn-sm", style={"fontSize": "10px"})
+                    ], className="d-flex mb-2"),
+                    html.Div([
+                        html.Button([
+                            html.I(className="fas fa-robot me-1"),
+                            "Start LLM"
+                        ], id="start-llm-btn", className="btn btn-info btn-sm me-1", style={"fontSize": "10px"}),
+                        html.Button([
+                            html.I(className="fas fa-stop me-1"),
+                            "Stop"
+                        ], id="stop-llm-btn", className="btn btn-warning btn-sm", style={"fontSize": "10px"})
+                    ], className="d-flex mb-2"),
+                    html.Small(id="text-export-status", children="Export: Stopped", className="text-muted d-block"),
+                    html.Small(id="llm-status", children="LLM: Stopped", className="text-muted d-block"),
+                    
                     html.Hr(className="my-2"),
                     html.Small("System Status", className="text-muted d-block mb-1"),
                     html.Div([